Region Normalization for Image Inpainting

Understand

Feature Normalization (FN) is an important technique to help neural network training, which typically normalizes features across spatial dimensions.

• Most previous image inpainting methods apply FN in their networks without considering the impact of the corrupted regions of the input image on normalization, e.g.
• mean and variance shifts.
• In this work, we show that the mean and variance shifts caused by full-spatial FN limit the image inpainting network training and we propose a spatial region-wise normalization named Region Normalization (RN) to overcome the limitation.